The present invention relates generally to biochemical data analysis, and more specifically to analysis of biochemical data using user-supplied parameters.
Biochemical experimental data analysis continues largely in a manual fashion. Users obtain experimental data on research conducted on biological samples, via various empirical means, including results of software program outputs. Such data can be voluminous with a wide variety of characteristics, and consequently cumbersome to manage and analyze. Current users often employ Excel, performing many manual steps for importing data into spreadsheets, for selecting categories of data from the entire dataset for evaluation and comparison, and for providing macros for statistical calculations and charting. Manual solutions are difficult for users to implement and manage, time consuming, error-prone, and a potential business risk.
Users do not currently have an easy to use interface and system for easily providing information about how to slice datasets, resulting in automatic updating of subsets of data, user views of statistical information and/or recalculations of data (e.g. statistics on the data and charts).
Therefore it is desirable to provide systems and methods that overcome the above and other problems.